After a wafer has been processed in a semiconductor manufacturing process, the integrated circuits (ICs) in the wafer are typically tested in automated test equipment (ATE). In an average production facility, there may be thousands of wafers produced per month, each wafer containing thousands of ICs, and each IC requiring hundreds of tests. The results (i.e., raw data, raw test data) of each IC may require kilobytes and megabytes of storage space. The raw test data for a wafer is stored on a per-wafer basis in a yield management system (YMS) database, for example. The amount of data stored in a common YMS database is therefore in the terabytes (i.e., more than 1012 bytes).
In addition to the collection of raw test data however, it is often necessary to perform further calculations to reveal trends hidden in the raw data. The computational bandwidth and the storage capacity needed to perform additional calculations of derived parameters (i.e., electrical fault density, random yield, and systematic yield), and aggregate data (i.e., wafer means or percentiles) in many yield management systems (YMS) may be limited or non-existent. In many cases, although a YMS may have the resources to calculate and store a limited number of derived parameters and aggregate data, the calculations are performed on a limited set of test data that do not span an extended period of time. Moreover, the data may be so vast that the calculations of derived parameters and aggregate data may not be performed in a timely manner, thus causing costly delays in the identification and the rectification of defective trends in the manufacturing process.
Identification and the rectification of defective trends in the manufacturing process may be accelerated by the calculating and storing of derived parameters and aggregated statistics with respect to regions (i.e., geographically defined spatial surface areas) in each wafer. Some YMS databases may perform limited calculations of statistical aggregated data for an entire wafer, but do not include calculations that would enable process monitoring on a wafer-by-wafer basis of regional statistical aggregated data.
Hence, there is a need for a method of aggregating regional data and storing the regionally aggregated data in a manner that provides user access to the regionally aggregated data at the time the data for the wafer is generated or stored in a large database such as a YMS database.